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VOL. 11, NO. 18, SEPTEMBER 2016 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
www.arpnjournals.com
10727
COMPARATIVE ANALYSIS FOR SOFTWARE TESTING: MOBILE
APPLICATIONS VERSUS WEB APPLICATIONS
Zainab Hassan Muhamad and Rosziati Ibrahim
Department of Software Engineering, Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia,
Parit Raja, Batu Pahat, Johor, Malaysia
E-Mail: zainab_hssn@yahoo.com
ABSTRACT
Software testing has an important role in software engineering, and is fundamental to Software Quality Assurance
(SQA). Besides the popularity of web applications, mobile applications have gained paralleled advancement despite
increasing complexity. On one hand, this issue reflects the rising concerns for ensuring performance both of web and
mobile applications. On the other hand, a comparative analysis of software testing issues between web and mobile
applications has not been completed. Thus, this study aims to employ an effective testing approach that is able to adapt
both of web and mobile application testing to detect possible failures. To achieve this, UML activity diagrams were
developed from four case studies for web and mobile applications to describe the behaviour of those applications. Test
cases were then generated by using the MBT technique from the developed UML activity diagrams. Performance
measurements Hits per Second, Throughput and Memory Utilization for each case study were evaluated by execution of
test cases that were generated by using HP LoadRunner 12.02 tool. Finally, the Mean Square Error (MSE) of performance
measurements was compared and analysed among the four case studies. The experimental results showed that the disparity
between the mobile applications and web applications was obvious. Based on the comparison analysis for software testing
of mobile applications versus web applications that was the web applications were lesser than mobile applications for
software testing of four case studies in terms each of the Hits per Second, Throughput and Memory Utilization.
Consequently, mobile applications need more attention in the testing process.
Keywords: software testing, mobile application testing, web application testing, model-based testing, unified modeling language.
INTRODUCTION
A Mobile application, also known as mobile
apps, is a software application that can be installed on
handheld devices, such as mobile phone, tablet, e-reader,
or other portable device. It is supported by operating
systems and is able to connect to wireless networks
(Gahran, 2011). While, a web application is an application
that is invoked by a client web browser over the Internet or
an Intranet. A web application allows the information
processing functions to be initiated remotely from a client
and executed partly on a web server, application server,
and/or database server. These applications are specifically
designed to be executed in a web-based environment. Web
applications are playing a very important role in many
business domains like retail, finance, sales, marketing and
management (Imran and Roopa, 2012).
Software testing has an important role in software
engineering, and is fundamental to Software Quality
Assurance (SQA). The objective of software testing is to
show the differences between the expected and actual
behaviors of the System under Test (SUT). Testing is
essential to the Software Development Life Cycle (SDLC)
that impacts the popularity of software and hardware (Ang
et al., 2014). The goal of software testing is to detect
whether the behavior of the system implemented has
visible differences from the expected behavior stated in
the specification (Sumit and Narendra, 2014). As in
software engineering, performance testing is performed to
determine how a system performs in terms of
responsiveness and stability under a particular workload. It
can also serve to investigate measure and validate quality
attributes of the system, such as scalability, reliability and
resource usage (Shilpa and Meenakshi, 2014). It is
concerned with achieving hits per second, throughput, and
resource utilization levels that meet the performance
objectives for the system. There are many tools that can be
used to simulate the load in terms of users, connections
and capture data related to hits per second, throughput, and
resource utilization. Among the most important tools is HP
LoadRunner (Sheetal and Joshi, 2012). There are various
parameters based on which performance of the system is
measured. They are known as performance measurements.
One is resource utilization, which is the number of
resources used to serve the user request. These resources
can be memory, processors, disk I/O and network
utilizations (Kalpan and Ramakanth, 2012). This study is
focused solely on resource utilization of memory.
Throughput is an important indicator for measuring server
performance, which represents the throughput capacity of
the server at any time. Generally, the higher the
throughput, the better the server performance will be. Hits
per second are the number of HTTP requests per second
that virtual users submit to the Web servers. It can reflect
whether or not the system is stable, when the number of
user’s increases, the hits per second will increase
accordingly (Weibiao et al., 2014).
The testing process is a very costly and time
consuming. In order to cut down on costs, save time, and
increase reliability, Model-Based Testing (MBT) approach
was used in this study. MBT is a process of generating test
cases and evaluating test results based on the design and
analysis of models. Recently, MBT has gained attention
with the popularization of modeling in software
development. The Unified Modeling Language (UML)
VOL. 11, NO. 18, SEPTEMBER 2016 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
www.arpnjournals.com
10728
modeling based testing approach intends to solve this
problem (Sandeep, Sangeeta and Gupta, 2012; Ang et al.,
2014). MBT is one of the most of significant techniques
that has been applied to generate test cases by using UML
diagrams for web applications by (Zhang, Rong and
Zhang, 2007; Ke, Xiao-Hong and Zhi-Yong, 2010;
Prachet and Abhishek, 2013). Moreover, MBT has been
applied to mobile applications by (Chouhan, Shrivastava
and Parminder, 2012; Tobias and Volker, 2014; Ang et al.,
2014). The UML activity diagrams support GUI modeling,
automated test case generation and error diagnosis. This
approach can reduce the overall test time, and can
effectively detect fatal faults in mobile applications (Ang
et al., 2014). In addition, the UML activity diagram is one
of the most important diagrams among the thirteen
diagrams. It is characterized by the high level of
abstraction compared to other diagrams like sequence
diagrams, class diagrams, etc. Furthermore, it is able to
represent loops and concurrent activities. UML activity
diagrams capture the key system behavior. The main
advantage of this model is its simplicity and ease of
understanding the flow of logic of the system as well. For
all these reasons, activity diagrams are well suited for
treating system level testing of web applications (Aye and
Myat, 2014).
Currently, mobile applications have parallel
advancement with web applications. This issue reflects the
rising concerns for ensuring performance both of web and
mobile applications (Maryam and Rosziati, 2014). As the
growth both of web and mobile applications is rapid, this
issue was interesting to some researchers (Vikas and
Rajesh, 2014; Prachet and Abhishek, 2013), and they have
taken into consideration web application testing. On the
other hand, other researchers (Tobias and Volker, 2014;
Ang et al., 2014) were focused on mobile application
testing. But, the comparative analysis between web
application testing and mobile application testing is an
issue that has not yet been resolved. Thus, the motivation
of this study is to employ an effective testing approach,
which is able to adapt with both web and mobile
application testing to discover failures in the required
performance. Therefore, the UML activity diagrams
developed from four case studies for web and mobile
applications to describe the behaviour of those
applications. Test cases then generated using the MBT
technique based on Test Case Generation based on
Activity Diagram (TCBAD) model from the developed
UML activity diagrams. In addition, performance
measurements Hits per Second, Throughput and Memory
Utilization for each case study were evaluated by
execution of test cases that were generated by using HP
LoadRunner tool. Finally, the performance measurements
Hits per Second, Throughput and Memory Utilization
compared and analysed among the case studies.
RELATED WORKS
Due to the lack of research on comparisons
between web applications testing and mobile application
testing, some of the research related to automated testing
and techniques will be reviewed in this section to generate
test cases for web and mobile applications. In addition to
the background of the work requirements for this study,
other related works that consist of similar efforts to
demonstrate the state-of-the-art in the test case generation
will also be presented. Most researchers were used the
MBT technique based on the UML activity diagrams, such
as Tobias and Volker (2014), Ang et al. (2014), Chouhan
et al. (2012) and Pakinam et al. (2011). While, the other
researchers, such as Vikas and Rajesh (2014) were used
sequence diagram and web diagram, and Prachet and
Abhishek (2013) were used use case diagram and activity
diagram.
Tobias and Volker (2014) proposed an approach
to test case generation and automated execution uses MBT
supported by UML activity diagrams to improve the
testing of context-aware mobile applications by reducing
test cases from design-time system models. Likewise, Ang
et al. (2014) proposed the AD Automation framework to
enable automated Graphical User Interface (GUI) testing
of smartphone applications based on UML activity
diagrams, which supports user behavior modeling and
automated GUI test case generation. This approach can
reduce the overall test time, testing efforts as well as
improving test adequacy. Moreover, this approach
effectively detects fatal faults in complex GUI
implementations and improves the quality of designs.
Also, Pakinam et al. (2011) proposed an automated
approach for generating test cases from UML Activity
diagram. The activity diagram is used to generate table
called Activity Dependency table (ADT) and convert it
into a directed graph called Activity Dependency Graph
(ADG). The algorithm proposed applies to the graph for
obtaining all the possible test paths. All the details are
added to each test path using the ADT to produce the final
test cases. Validating the generated test cases was
achieved by Cyclomatic complexity. The proposed model
was applied to three different case studies of web
applications. Chouhan et al. (2012) proposed Test Case
Generation based on Activity Diagram (TCBAD) using
MBT for mobile application. This approach was extended
from previous study by Pakinam et al. (2011) for web
application. TCBAD model proposed uses MBT for
mobile application based on activity diagram, that were
used in representing the workflows of stepwise activity
and actions with support for choice, iteration and
concurrently, the complexity was calculated using
Cyclomatic Complexity. The proposed model
automatically creates ADT from activity diagram, and
then uses it to create ADG. TCBAD algorithm is
introduced to generate test paths from ADG. Finally the
test paths with the ADT are used to generate the final test
cases. The proposed model saves time and effort and also
increases the quality of generated test cases.
Vikas and Rajesh (2014) proposed an approach
uses MBT supporting UML diagrams, namely sequence
and web diagrams, for test case generation for web
applications. Web diagrams provide the functional
requirements and sequence diagrams provided the
navigation web application in terms dynamic behavior of
the application under test. The proposed approach
VOL. 11, NO. 18, SEPTEMBER 2016 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
www.arpnjournals.com
10729
automatically generates test cases, overcomes problems
related to omitted data, captures the dynamic behavior of
web applications and improves test case information.
While, Prachet and Abhishek (2013) proposed an
approach uses MBT supporting UML diagrams, namely
use case diagrams and activity diagrams, to generate and
prioritize test cases for regression testing of web
application. This approach combined activity diagrams to
get a clearer picture of test case generation and effective
coverage path of those test cases.
The overall summary is described in tabular form
for a quick review and comparison of the testing
techniques. Table-1 shows a comparative summary of the
related works for mobile application testing. Table-2
shows a comparative summary of the related works for
web application testing.
Table-1. Review of the comparison of testing techniques of the related works regarding to mobile applications.
Author (Year) Technique UML diagram Conclusion
Tobias and
Volker (2014)
Model-Based
Testing
Activity
Diagram
The proposed approach can reduce
test cases from design-time system
models.
Ang et al.
(2014)
Model-Based
Testing
Activity
Diagram
The proposed approach can reduce
the overall test time, testing efforts
as well as improving test
adequacy.
Chouhan et al.
(2012)
Model-Based
Testing
Activity
Diagram
The proposed approach model
saves time and effort and also
increases the quality of generated
test cases.
Table-2. Review of the comparison of testing techniques of the related works regarding to web applications.
Author (Year) Technique UML diagram Conclusion
Vikas and
Rajesh (2014) Model-Based Testing
Sequence Diagram
and
Web Diagram
The proposed approach captures
the dynamic and improves test
case information.
Prachet and
Abhishek (2013) Model-Based Testing
Use Case Diagram
and Activity
Diagram
The proposed approach can get a
clearer picture of test case
generation and effective coverage
path of those test cases.
Pakinam et
al.(2011) Model-Based Testing Activity Diagram
The proposed approach can save
time, effort and increasing the
overall testing process
performance.
Table-1 and Table-2 show the techniques and
various UML diagrams that were used for mobile
application testing and web application testing. Most
researchers used MBT technique and UML activity
diagrams for mobile application testing and web
application testing. This approach can reduce the overall
test time, testing efforts as well as improving test
adequacy. UML activity diagrams are one of the important
UML models used in representing the workflows of
stepwise activities and actions with support for choice,
iteration and concurrency. Moreover, UML activity
diagrams can be utilized to describe the business and
operational step-by-step workflows of components in a
system, as it has all the characteristics that can improve the
quality of the automatically generated test cases (Pakinam
et al., 2011). Therefore, based on related works, TCBAD
model to generate test cases based on UML activity
diagram was used in this study as proposed by Chouhan et
al. (2012).
METHODOLOGY
In this study four phases are undertaken, as
shown in Figure-1. These phases are detailed and
discussed in the following:
Phase 1 (Developing UML activity diagrams): The
flexibility in describing various control flows makes UML
activity diagram a promising candidate for application
behavior modeling, reducing overall testing efforts as well
as improving test adequacy. The application behavior
derivation and its depiction using UML activity diagrams
to describe either sequential or concurrent workflows of
stepwise activities and actions (Aye and Myat, 2014). This
study used the TCBAD model (Chouhan et al., 2012) of
four case studies of the mobile and web applications. The
TCBAD model includes the development of the UML
activity diagram to describe the application behaviour,
which transforms the UI to the UML activity diagram. The
overall activity diagram describes the business and
operational activities step-by-step for all of the main
VOL. 11, NO. 18, SEPTEMBER 2016 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
www.arpnjournals.com
10730
functions in the application interface. The case studies are
eBook store, namely Inktera Books and Kobo Booksfor
mobile applications, which are available at Google play
apps. While, Inktera and Kobo for web applications, which
are available at (https://www.inktera.com,
http://www.kobobooks.com). All case studies have same
main functions, namely Sign in, Search, Browse and
Library.
Phase 2 (Generating test cases using mbt technique
based on activity diagram): The test cases were
generated from four case studies for web and mobile
applications by using the MBT technique based on
TCBAD model proposed by Chouhan et al. (2012). This
model used to generate test cases based on activity
diagrams developed. TCBAD model includes four steps
after application behavior modeling by using UML
activity diagrams. Its steps are generation of ADT (The
ADT has six columns as shown in Table-3), generation of
ADG (The ADG is generated automatically from the ADT
constructed), generation of test paths based on the TCBAD
algorithm as shown in Figure-2 and validation number of
test paths based on Equation (1) of the Cyclomatic
Complexity (CC) (Agarwal et al., 2010), and finalthe test
paths with the ADT are used to generate the final test
cases.
Phase 3 (Evaluation of performance measurements):
HP LoadRunner 12.02 tool (HP Loadrunner, 2015) is able
to monitor and assess the real-time performance for both
of mobile applications and web applications. The usage of
HP LoadRunner 12.02 tool can shorten test time in
maximum limit and optimize performance (Prakash and
Gopala, 2012). The HP LoadRunner 12.02 tool was used
to evaluate performance measurements Hits per second,
Throughput and Memory utilization by execution of test
cases generated and to achieve the results for each case
study.
Phase 4 (Comparative analysis): The results were
compared and analyzed after they obtained values of the
each Hits per second, Throughput and Memory utilization
by execution of the test cases generated of four case
studies by the HP LoadRunner 12.02 tool. The Mean
Square Error (MSE) is defined as (Huang and Kuo, 2002)
in this quantitative comparison; MSE was used because it
is easier to understand. A smaller MSE indicates a smaller
fitting error, and better overall performance. The MSE
values of the each Hits per second, Throughput and
Memory utilization were considered as comparison criteria
the differences and similarities among the case studies of
web and mobile applications based on Equation (2)
(Salkind, 2010).
Figure-1. Research framework.
Table-3. Activity dependency table. (Chouhan
et al., 2012).
NO
Vertex
Activity Name
Dependency
nodes
In degree value
Dependent
nodes
Out degree
values
Figure-2. The TCBAD algorithm for generating the test
paths. (Chouhan et al., 2012).
VOL. 11, NO. 18, SEPTEMBER 2016 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
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10731
(1)
E = Number of Edges,
N = Number of Nodes.
(2)
N = Number of Values,
Y = Actual Value,
= Estimated Value.
COMPARATIVE ANALYSIS
According to the results obtained by applying
MBT technique based on the TCBAD model using UML
activity diagrams on four case studies of mobile and web
applications in order to performance testing. The testing
process was dependent on the execution of the test cases
generated by using the HP Loadrunner tool. The MSE for
each measurement is considered as comparison criteria in
this study. Table-4 shows the comparative analysis of the
MSE value of the Hits per second, Throughput and
Memory utilization for each case study of mobile and web
applications.
Table-4.Comparative analysis of case studies of mobile
and web applications.
Application Type
MSE
(Hits per
Second)
MSE
(Throughput)
MSE
(Memory
Utilization)
Mobile Applications
Case
study 1 0.3795 0.00002 16.06727
Case
study 2 0.3237 0.00002 15.42017
Web
Applications
Case
study 3 0.23955 0.00002 14.21717
Case
study 4 0.24762 0.00001 12.26179
Figure-3. Comparative analysis diagram for case studies
of mobile and web applications of the MSE value of the
Hits per second.
Figure-3 shows the comparative analysis of the
MSE value based on the Hits per Second for mobile and
web applications. Where the MSE of the Hits per Second
of Case Study 1 of mobile application is 0.3795 and Case
Study 3 of web application is 0.23955, while Case Study 2
of mobile application is 0.3237 and Case Study 4 of web
application is 0.24762. This implies that there is a
difference in performance between mobile applications
and web applications in terms of measurement of the Hits
per Second. The Case Study 3 has the smallest MSE of the
Hits per Second. This indicates that Case Study 3 of the
web application has the smallest fitting error, and better
performance in terms the number of HTTP requests sent to
the web server during a specific time period of the
performance test.
Figure-4. Comparative analysis diagram for case studies
of mobile and web applications of the MSE value of
the throughput.
Figure-4 shows the comparative analysis based
on the MSE value of the Throughput for mobile and web
application. The MSE of the Throughput for Case study 1
of mobile application is 0.00002. It is similar to Case
Study 3 of web application. While the MSE of the
Throughput for Case Study 2 of mobile application is
0.00002 and Case Study 4 of web application is 0.00001.
This implies that there is slightly different in performance
between mobile applications and web applications in terms
of measurement of the Throughput. The Case Study 4 has
VOL. 11, NO. 18, SEPTEMBER 2016 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
www.arpnjournals.com
10732
the smallest MSE of the Throughput. This indicates that
Case Study 4 of the web application has the smallest
fitting error and better performance in terms the server
response during a specific time period of the performance
test.
Figure-5. Comparative analysis diagram for case studies
of mobile and web applications of the MSE value of the
memory utilization.
Figure-5 shows the comparative analysis based
on the MSE value of the Memory utilization for mobile
and web application. The MSE of the Memory utilization
of Case Study 1 of mobile application is 16.06727 and
Case Study 3 of web application is 14.21717, while Case
Study 2 of mobile application is 15.42017 and Case Study
4 of web application is 12.26179. This implies that there is
a difference in performance between mobile applications
and web applications in terms of measurement of the
Memory utilization. The Case study 4 has the smallest
MSE of the Memory utilization. This indicates that Case
Study 4 of the web application has the smallest fitting
error, and better performance in terms the percentage of
memory used during the scenario execution of the
performance test.
In terms of mobile and web applications, the
comparison has been made for Case Study 1 (of mobile
application) with Case Study 3 (of web application) based
on number of test paths, number of test cases and MSE of
performance measurements: Hits per Second, Throughput
and Memory Utilization, as shown in Table-5. Likewise,
the comparison has been made for Case Study 2 (of
mobile application) with Case Study 4 (of web
application), as shown in Table-6.
Overall, the comparative analysis indicates that
the variation was clearly between the case studies of both
mobile and web applications in terms of the number of test
paths, number of test cases, MSE of Hits per Second, MSE
of Throughput and MSE of Memory Utilization. This
implies, the mobile applications, in terms of the number of
test paths and number of test cases lesser than web
applications. On the other hand, the mobile applications, in
terms of the MSE criterion have high Hits per Second,
high Throughput and high Memory Utilization, which
means that the mobile applications have poor performance
compared to web applications. It can be concluded, taking
into consideration more emphasis on the mobile testing.
Table-5. The comparative analysis between Case Study 1
(of mobile application) with Case Study 3 (of web
application).
The comparison
criteria
Case study 1
(mobile app)
Case study 3
(web app)
Number of Test Paths 19 23
Number of Test cases 19 23
MSE of
Performance
Measurements
Hits per
Second 0.3795 0.23955
Throughput 0.00002 0.00002
Memory
Utilization 16.06727 14.21717
Table-6. The comparative analysis between case study 2
(of mobile application) with case study 4 (of web
application).
The Comparison
Criteria
Case Study 2
(mobile app)
Case Study 4
(web app)
N
umber of Test Paths 21 22
N
umber of Test cases 21 22
MSE of
Performance
Measurements
Hits per
Second 0.3237 0.24762
Throughput 0.00002 0.00001
Memory
Utilization 15.42017 12.26179
CONCLUSIONS
The number of mobile and web applications is
growing rapidly, which creates an impetus for researchers
and developers to come up with adaptation testing
techniques for both of these kinds of applications to ensure
their reliability. The MBT approach can generate highly
efficient test cases with the minimum number of steps,
saving time, effort and increasing the quality of generated
test cases thus improving the overall testing process
performance. Moreover, it includes validation of the
number of generating test paths during the generation
process to ensure their coverage. In addition, the UML
activity diagram is considered a de-facto standard for
development models and its usage is widespread in the
testing process according to related works. During the
practical experience in this study by using activity diagram
for each of mobile applications and web applications,
which is showing that there are some difficulties when
transforming the UI to the activity diagram in the
applications of mobile compared to the web application,
because, there were a fundamental differences between
mobile applications and web applications in terms of
navigation in the UI. However, this study has been
achieved its objectives.
The experimental results showed that the
disparity between the mobile applications and web
applications was obvious. Based on the comparison
analysis for software testing of mobile applications versus
web applications that was the web applications were lesser
than mobile applications for software testing of four case
VOL. 11, NO. 18, SEPTEMBER 2016 ISSN 1819-6608
ARPN Journal of Engineering and Applied Sciences
©2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
www.arpnjournals.com
10733
studies in terms each of the Hits per second, Throughput
and Memory utilization. Consequently, mobile
applications need more attention in the testing process.
In future work, the authors may aim to expand
work to developing more specific software testing tool for
mobile applications.
ACKNOWLEDGEMENTS
Firstly, I would like to express my sincere
gratitude to my supervisor, Prof. Dr. Rosziati Ibrahim, for
the continuous support, motivation, and immense
knowledge. Also, I would like to express my deepest
gratitude to Universiti Tun Hussein Onn Malaysia
(UTHM), and especially the Faculty of Computer Science
and Information Technology / Department of Software
Engineering for giving me the opportunity to further my
Master’s degree.
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